Question

I have a list that contains many dictionaries. Each dictionary represents a change that has occurred within my application. The “change” dictionary has the following entries:

userid: The user ID for a user
ctype: A reference to a change type in my application
score: A score

The ctype can be one of about 12 different strings to include “deletion”, “new”, “edit” and others. Here is an example of one of the “change” dictionaries:

{'userid':2, 'score':10, 'ctype':'edit'}

My question is, how can I create a dictionary that will aggregate all of the change types for each user within this large list of dictionaries? I would like to add the score from each change dictionary to create a total score and add each ctype instance together to get a count of each instance. The goal is to have a list of dictionaries with each dictionary looking like this:

{'userid':2, 'score':325, 'deletion':2, 'new':4, 'edit':9}

I have been trying to work this out but I am pretty new to python and I wasn’t sure how to count the actual change types. The other part that gets me is how to refer to a dictionary based on ‘userid’. If someone can present an answer I am sure that all of this will become very apparent to me. I appreciate any and all help.

Answer 1

The key thing to agregate data here is to have a dictionary where each key is the userid, and each entry is the data relevant to that userid.

final_data = {}
for entry in data:
    userid = entry["userid"]
    if userid not in final_data:
        final_data[userid] = {"userid": userid, "score": 0} 
    final_data[userid]["score"] += entry["score"]
    if not entry["ctype"] in final_data[userid]:
        final_data[userid][entry["ctype"]] = 1
    else:
        final_data[userid][entry["ctype"]] += 1

If you want the result as a list of dictionaries, just use final_data.values()